Security Software Engineer (tdr)

ByteDance ByteDance · Big Tech · San Jose, CA · R&D

Security Software Engineer focused on threat detection and response (TDR) for large-scale platforms, with a specific emphasis on securing AI and LLM systems, including agent architectures. The role involves designing and building defensive frameworks, identifying attack surfaces, and ensuring the safe deployment of AI-powered products.

What you'd actually do

  1. Drive the security of LLM-based systems and AI agent architectures — identifying novel attack surfaces, developing defensive frameworks, and ensuring the safe deployment of AI-powered products at scale.
  2. Design and build innovative threat detection, prevention, and response (TDR) systems that protect large-scale platforms, critical infrastructure, and globally distributed endpoints.
  3. Own the end-to-end lifecycle of distributed security systems operating across global regions — from deployment and capacity planning through production reliability, observability, and continuous iteration at scale.
  4. Partner closely with cross-functional global teams to turn vague problem statements and emerging threat patterns into clear product requirements, and ship high-impact security capabilities on aggressive timelines.

Skills

Required

  • Bachelor's degree or above in Computer Science, Computer Engineering, or related fields
  • at least 3 years of hands-on software development experience
  • Strong fundamentals in algorithms and data structures
  • proficiency in Go, Java, or Rust
  • ability to write clean, reliable, and production-ready code
  • Strong back-end development skills
  • experience with cloud-native infrastructure
  • networking
  • building services that run reliably at scale
  • Hands-on experience using AI-assisted and agentic development workflows
  • Proven ability to think critically, break down complex or ambiguous problems, and formulate clear, practical solutions in a timely manner

Nice to have

  • Experience designing and implementing threat detection and response (TDR) systems
  • detection engineering
  • automated response pipelines
  • integration with modern security architectures
  • Familiarity with security challenges in LLM-based systems or AI agent architectures
  • prompt injection
  • model abuse
  • tool-use exploitation
  • securing agentic workflows
  • Hands-on experience with cloud-native infrastructure (e.g., Kubernetes, observability stacks)
  • large-scale streaming/batch data pipelines
  • building distributed systems that power real-time detection and prevention at scale
  • Experience working in globally distributed teams
  • driving cross-functional projects end-to-end
  • Demonstrated ability to lead technical initiatives
  • mentor engineers
  • influence security direction beyond your immediate team

What the JD emphasized

  • security of LLM-based systems and AI agent architectures
  • safe deployment of AI-powered products at scale
  • security challenges in LLM-based systems or AI agent architectures
  • prompt injection
  • model abuse
  • tool-use exploitation
  • securing agentic workflows

Other signals

  • AI/LLM system security
  • defensive frameworks for AI
  • safe deployment of AI-powered products
  • security challenges in LLM-based systems or AI agent architectures